#Sprint 02 - "Student Name"
What went well:
- Example: "Great use of crosstab! Excellect use of variables"
<code here=""></code>| const LoginPage = () => { | |
| const logo = "/assets/images/no-placeholder/logo.png" | |
| return ( | |
| <Fragment> | |
| <Head> | |
| <title>Login - [Store Name] </title> | |
| </Head> |
| # # 1 | |
| def factorial(n): | |
| current = 0 | |
| if n == 0: | |
| print("0") | |
| else: | |
| for i in range(1, n+1): | |
| current = current * i |
| songs = ["ROCKSTAR", "Do It", "For The Night"] | |
| print(songs[1]) | |
| # will print ROCKSTAR and Do It | |
| print(songs[0:2]) | |
| #print "Do it" and "for the night" | |
| print(songs[1:3]) |
| def area(width, height): | |
| result = width * height | |
| return result | |
| result = area(5, 6) | |
| print(result) | |
| print(area(4, 3)) | |
| print(area(2, 3)) |
| class ElecScooterRental: | |
| def __init__(self,stock=0): | |
| """ | |
| Our constructor class that instantiates scooter rental shop. | |
| """ | |
| self.stock = stock | |
| def displaystock(self): |
| int hIndex(int[] citations) { | |
| int len = citations.length; | |
| if (len == 0) { | |
| return 0; | |
| } | |
| if (len == 1) { | |
| if (citations[0] == 0) { | |
| return 0; |
| import sys | |
| from typing import List, Any, Tuple, Union | |
| class KnightsTravails: | |
| def __init__(self, width, height): | |
| self.w = width | |
| self.h = height | |
| self.board = [] |
| # Note – this is not a bash script (some of the steps require reboot) | |
| # I named it .sh just so Github does correct syntax highlighting. | |
| # | |
| # This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5 | |
| # | |
| # The CUDA part is mostly based on this excellent blog post: | |
| # http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/ | |
| # Install various packages | |
| sudo apt-get update |
| import pandas as pd | |
| import numpy as np | |
| import tensorflow as tf | |
| import re | |
| from nltk.corpus import stopwords | |
| import time | |
| clean_texts = [] | |
| for text in dataset.review: | |
| clean_texts.append(clean_text(text)) |